Ethics statement
The present study used previously collected anonymized and de-identified data from the SEER database. Therefore, no additional informed consent was required. The study was complied with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards and deemed exempt from review by the Ethics Board of the Tianjin Chest Hospital.
Data source
The data used in the present study were abstracted from the SEER 18 registries research database (Nov 2020 Sub, 2000-2018), comprising approximately 30% of the total US population. The information of metastatic sites of brain, bone, liver, and lung were not collected until 2010. So, esophageal cancer patients diagnosed between 2010 and 2018 were included in the present study to analyze brain metastases risk factors. Esophageal cancer patients diagnosed between 2010 and 2017, with a follow-up at least for 1 year, were retrieved to investigate the prognostic factors of esophageal cancer patients with brain metastases. The SEER-stat software (the Surveillance Research Program, National Cancer Institute SEER Stat software, www.seer.cancer.gov/seerstat, Version 8.3.9) was used to generate the case listing.
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Cohort selection
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The inclusion criteria were as follows: the site recodes ICD-O-3 (International Classification of Diseases for Oncology-3)/WHO 2008 was “Esophagus”; the behavior recode for analysis was “Malignant”; diagnosed between 2010 and 2018. The exclusion criteria were as follows: diagnosis obtained from a death certificate or an autopsy; unknown information for brain metastases, or follow-up. The flow-chart for the study population selection was shown in Fig. 1.
Statistical analysis
Patients’ demographic and clinical features were collected including age, sex, race, primary site, histology type, grade, T stage, N stage, and the presence of bone metastases, liver metastases, lung metastases and survival time. Quantitative data were described as mean ± standard deviation (SD). Categorical data were presented as number and the percentage (N, %). The differences in the brain metastases incidence between the categorical variables were analyzed by Pearson’s chi-square test or rank sum test. The univariable and multivariable logistic regression model were conducted to determine the risk factors of brain metastases. Factors with a P-value less than 0.05 in the univariable logistic regression analysis were incorporated into the multivariable regression model.
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A nomogram predicting brain metastases was formulated based on the results of multivariable logistic analysis using the rms package in R software (Version 3.4.2; https://www.R-project.org). The performance of the nomogram was evaluated by the receiver operating characteristics (ROC). Calibration curves were plotted to assess the calibration of the nomogram. Harrell’s C-index was measured to quantify the discrimination performance of the nomogram. The nomogram was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate a relatively corrected C-index [8].
The overall survival was analyzed using the Kaplan-Meier method with the log-rank test. The univariable and multivariable Cox regression model were conducted to determine the prognostic factors for patients with brain metastases. Factors with a P-value less than 0.05 in the univariable regression analysis were incorporated into the multivariable regression model.
All statistical analyses were performed using the R software (Version 3.4.2; https://www.R-project.org). Two-sided P < 0.05 were considered as statistically significant.
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